Key Takeaway:
Click each topic to view the key takeaway for that section and learn how FPI and FPWI translate environmental data into operational wildfire danger metrics.
How the FPI Model Works
Understanding Fire Potential Index (FPI)
Operational Applications and Real-World Use
The FPI system includes multiple components designed to provide both raw fire danger estimates and historical context. Raw FPI values estimate wildfire potential based on current conditions, while historical percentiles compare those conditions to past climate patterns. These are combined into the FPI Composite Index, a simplified scale from 1 to 5.
Technosylva’s FPI model uses high-resolution environmental data and real wildfire observations to estimate wildfire potential. The model incorporates factors such as live and dead fuel moisture, wind speed, drought conditions, soil moisture, and snow cover.
The FPI Suite: Components of the Model
FPI Model Development
Model Validation and Performance
Fire Potential Wind Index (FPWI)
The Fire Potential Wind Index expands the FPI framework by incorporating wind gust percentiles. This helps identify scenarios where strong winds combine with flammable fuels, increasing the likelihood of wind-driven wildfires and power line ignitions.
The FPI model has been validated using more than 500,000 historical fires and 10,000 power line ignitions. Results show that larger fires, greater burn areas, and more damaging events consistently occur during Elevated, High, and Extreme FPI conditions, confirming the model’s ability to identify dangerous wildfire environments.
FPI History and Core Concepts
Fire Danger vs. Fire Risk
The Fire Potential Index was originally developed by utilities to provide a daily indicator of wildfire danger for operational planning. Technosylva has since expanded the model using advanced data science and large wildfire datasets to improve accuracy and applicability across different regions.
Fire danger refers to the environmental conditions that influence ignition and fire spread, while fire risk considers the probability and consequences of a wildfire impacting people, infrastructure, or assets. FPI measures environmental danger, while risk models assess potential impacts.
Utilities use FPI and FPWI to guide operational decisions such as adjusting work practices, modifying protection settings, or evaluating Public Safety Power Shutoff (PSPS) actions. These metrics help organizations understand daily wildfire danger conditions across their service territories.
Analysis of wildfire damage shows that most building losses occur during the highest FPI levels. As fire potential increases, the likelihood of severe structural damage also rises, demonstrating the relationship between extreme environmental conditions and wildfire consequences.
Operational Use for Utilities
Building Damage and Fire Consequences
Integrating FPI with Risk Modeling
Case Studies: Real Wildfire Events
Case studies of major wildfires, including the Marshall Fire and Smokehouse Creek Fire, show how FPI and FPWI successfully identified extreme conditions during critical periods before and during wildfire events.
FPI and FPWI provide the environmental context for wildfire danger, while risk modeling tools identify where potential impacts may occur. When combined, these metrics allow utilities to make more precise, data-driven operational decisions.
October 2025 Technosylva's Fire Potential Index (FPI) Key Takeaway
Andrew Black
Created on March 10, 2026
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Transcript
Key Takeaway:
Click each topic to view the key takeaway for that section and learn how FPI and FPWI translate environmental data into operational wildfire danger metrics.
How the FPI Model Works
Understanding Fire Potential Index (FPI)
Operational Applications and Real-World Use
The FPI system includes multiple components designed to provide both raw fire danger estimates and historical context. Raw FPI values estimate wildfire potential based on current conditions, while historical percentiles compare those conditions to past climate patterns. These are combined into the FPI Composite Index, a simplified scale from 1 to 5.
Technosylva’s FPI model uses high-resolution environmental data and real wildfire observations to estimate wildfire potential. The model incorporates factors such as live and dead fuel moisture, wind speed, drought conditions, soil moisture, and snow cover.
The FPI Suite: Components of the Model
FPI Model Development
Model Validation and Performance
Fire Potential Wind Index (FPWI)
The Fire Potential Wind Index expands the FPI framework by incorporating wind gust percentiles. This helps identify scenarios where strong winds combine with flammable fuels, increasing the likelihood of wind-driven wildfires and power line ignitions.
The FPI model has been validated using more than 500,000 historical fires and 10,000 power line ignitions. Results show that larger fires, greater burn areas, and more damaging events consistently occur during Elevated, High, and Extreme FPI conditions, confirming the model’s ability to identify dangerous wildfire environments.
FPI History and Core Concepts
Fire Danger vs. Fire Risk
The Fire Potential Index was originally developed by utilities to provide a daily indicator of wildfire danger for operational planning. Technosylva has since expanded the model using advanced data science and large wildfire datasets to improve accuracy and applicability across different regions.
Fire danger refers to the environmental conditions that influence ignition and fire spread, while fire risk considers the probability and consequences of a wildfire impacting people, infrastructure, or assets. FPI measures environmental danger, while risk models assess potential impacts.
Utilities use FPI and FPWI to guide operational decisions such as adjusting work practices, modifying protection settings, or evaluating Public Safety Power Shutoff (PSPS) actions. These metrics help organizations understand daily wildfire danger conditions across their service territories.
Analysis of wildfire damage shows that most building losses occur during the highest FPI levels. As fire potential increases, the likelihood of severe structural damage also rises, demonstrating the relationship between extreme environmental conditions and wildfire consequences.
Operational Use for Utilities
Building Damage and Fire Consequences
Integrating FPI with Risk Modeling
Case Studies: Real Wildfire Events
Case studies of major wildfires, including the Marshall Fire and Smokehouse Creek Fire, show how FPI and FPWI successfully identified extreme conditions during critical periods before and during wildfire events.
FPI and FPWI provide the environmental context for wildfire danger, while risk modeling tools identify where potential impacts may occur. When combined, these metrics allow utilities to make more precise, data-driven operational decisions.